Paper Info
Title
Knowledge representation for the intelligent legal case retrieval
Abstract
In this paper, we develop a knowledge representation model for the intelligent retrieval of legal cases, which provides effective legal case management. Examples are taken from the domain of accident compensation. A new set of sub-elements for legal case representation has been developed to extend the traditional representation elements of issues and factors. In our model, an issue may need to be further decomposed into sub-issues, and factors are categorized into pro-claimant, pro-responder and neutral factors. These extensions can effectively reveal the factual relevance between legal cases. Based on the knowledge representation model, we propose the IPN algorithm for intelligent legal case retrieval. Experiments and statistical analysis have been conducted to demonstrate the effectiveness of the proposed representation model and the IPN algorithm.
Year
DOI
Venue
2005
10.1007/11552413_49
KES (1)
Keywords
Field
DocType
effective legal case management,legal case,ipn algorithm,accident compensation,proposed representation model,intelligent legal case retrieval,legal case representation,knowledge representation model,intelligent retrieval,traditional representation element,statistical analysis,knowledge representation
Knowledge representation and reasoning,Legal case,Information retrieval,Computer science,Artificial intelligence,Knowledge base,Alternative dispute resolution,Case-based reasoning,Legal precedent,Distributed computing,Statistical analysis
Conference
Volume
ISSN
ISBN
3681
0302-9743
3-540-28894-5
Citations 
PageRank 
References 
5
0.45
7
Authors
4
Name
Order
Citations
PageRank
Yiming Zeng1252.61
Ruili Wang244650.35
john zeleznikow351377.54
Elizabeth Kemp45810.49